刘振华, 张林, 罗远婵, 张道敬, 李元广. 基于极端顶点混料试验设计的多粘类芽孢杆菌可湿性粉剂载体优化[J]. 农药学学报, 2014, 16(4): 445-451. DOI: 10.3969/j.issn.1008-7303.2014.04.12
    引用本文: 刘振华, 张林, 罗远婵, 张道敬, 李元广. 基于极端顶点混料试验设计的多粘类芽孢杆菌可湿性粉剂载体优化[J]. 农药学学报, 2014, 16(4): 445-451. DOI: 10.3969/j.issn.1008-7303.2014.04.12
    shu
    LIU Zhenhua, ZHANG Lin, LUO Yuanchan, ZHANG Daojing, LI Yuanguang. Optimization of Paenibacillus polymyxa wettable powder based on the extreme vertex mixture design[J]. Chinese Journal of Pesticide Science, 2014, 16(4): 445-451. DOI: 10.3969/j.issn.1008-7303.2014.04.12
    Citation: LIU Zhenhua, ZHANG Lin, LUO Yuanchan, ZHANG Daojing, LI Yuanguang. Optimization of Paenibacillus polymyxa wettable powder based on the extreme vertex mixture design[J]. Chinese Journal of Pesticide Science, 2014, 16(4): 445-451. DOI: 10.3969/j.issn.1008-7303.2014.04.12
    shu

    基于极端顶点混料试验设计的多粘类芽孢杆菌可湿性粉剂载体优化

    Optimization of Paenibacillus polymyxa wettable powder based on the extreme vertex mixture design

      摘要
    • 摘要: 润湿性是衡量可湿性粉剂质量的重要指标。首先通过在轻质碳酸钙载体中添加质量分数为10%的白炭黑，使多粘类芽孢杆菌可湿性粉剂的润湿时间由416 s缩短到54 s，在此基础上，利用混料试验设计优化了多粘类芽孢杆菌可湿性粉剂的载体配方。结果表明：多粘类芽孢杆菌可湿性粉剂载体中合适的轻质碳酸钙质量分数为90%~92%，白炭黑为7.5%~9.0%，用高岭土代替部分轻质碳酸钙有利于降低制剂pH，但不利于制剂润湿性的提高。混料试验设计预测优化载体配方条件下多粘类芽孢杆菌可湿性粉剂的润湿时间为85~117 s，悬浮率为70.5%~71.7%，pH为9.01~9.05，验证试验结果和预期结果能够较好地吻合。研究结果可供可湿性粉剂载体的优化参考。

       

      Abstract: Wettability is an important quality performance of wettable powder (WP). In this study, 10% (mass fraction) precipitated silica (PS) in light calcium carbonate (LCC) was used to reduce wetting time of Paenibacillus polymyxa WP (PPWP) from 416 s to 54 s. Then, extreme vertex mixture design was used to optimize PPWP formulation. Optimization results showed that suitable LCC mass fraction in PPWP carrier was 90%-92%, suitable PS mass fraction was 7.5%-9.0%. Under these conditions, mixture design predicted that wetting time of PPWP would be 85-117 s, suspensibility of PPWP would be 70.5%-71.7%, and pH value of PPWP would be 9.01-9.05. Verification test results matched well with the predicted results, which will provide reference for optimization of PPWP.

       

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